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PhysicsNeMo General Release v2.0.0

đź“ť NVIDIA PhysicsNeMo v2.0 contains significant reorganization of all the features, with easier installation and integration to external packages. See the migration guide for more details!

Added

  • Refactored diffusion preconditioners in physicsnemo.diffusion.preconditioners relying on a new abstract base class BaseAffinePreconditioner for preconditioning schemes using affine transformations. Existing preconditioners (VPPrecond, VEPrecond, iDDPMPrecond, EDMPrecond) reimplemented based on this new interface.
  • New physicsnemo.experimental.nn.symmetry module that implements building blocks that preserve 2D and 3D rotational equivariance using a grid-based layout for efficient GPU parallelization, and an emphasis on compact einsum operations.

Changed

  • PhysicsNemo v2.0 contains significant reorganization of tools. Please see the v2.0-MIGRATION-GUIDE.md to understand what has changed and why.
  • DiT (Diffusion Transformer) has been moved from physicsnemo.experimental.models.dit to physicsnemo.models.dit.

Fixed

  • Shape mistmatch bug in the Lennard Jones example

Dependencies

  • CUDA backend is now selected via orthogonal cu12 / cu13 extras rather than being hardcoded to CUDA 13. Feature extras (nn-extras, utils-extras, etc.) are now CUDA-agnostic and can be combined with either backend, e.g. pip install "nvidia-physicsnemo[cu13,nn-extras]". When neither cu12 nor cu13 is specified, PyTorch is installed from PyPI using its default build (currently CUDA 12.8 on Linux). For development with uv, use uv sync --extra cu13 (or --extra cu12) to select the backend.

Contributors

We’re grateful to everyone who contributed issues, feature ideas, fixes, and documentation updates — your input is what helps us continuously improve PhysicsNeMo for the whole community! A special shout-out to the authors of the pull requests listed above, in no particular order:

@jleinonen @dran-dev @aayushg55 @saikrishnanc-nv @jeis4wpi @albertocarpentieri @paveltomin @weilr @giprayogo @tonishi-nv @younes-abid @dakhare-creator @Alexey-Kamenev

Thank you :heart: — we truly appreciate your contributions and hope to see more from you in the future!

Source: README.md, updated 2026-03-09